Knowledge-Driven Predictive Framework for Digital Addiction: Integrating Ethical and Philosophical Dimensions of AI

Abstract

Many countries are concerned about how quick digital addiction is becoming, especially for younger people and those with jobs. AI can predict and shape behavior effectively, but current models usually do not consider important ethical issues. The research puts forward a framework that uses expert systems and ontological reasoning to locate patterns of digital addiction. The framework also adds ethical considerations, such as fairness and respect for personal autonomy, and turns to Kantian deontology and virtue ethics to guide AI decisions. By applying machine learning techniques and symbolic logic and using real data from people's actions, the model has better prediction results and follows ethical standards. The study participates in the interdisciplinary conversation on responsible AI and provides practical support for those working on digital addiction.

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